Build, evaluate, and explain your first predictive models.
Learn supervised learning, model evaluation, feature thinking, and practical ML workflows with Python.
Learning outcomes
Features / Train/Test Split / Regression / Classification / Model Evaluation / Prediction / Metrics / Feature Importance / Overfitting / Interpretation
Course syllabus
Explore the topics, practice activities, and outputs in each module.
3 modules / 8 weeks / Instructor-led
Explore the curriculum
Projects
These course assignments use practice datasets and business scenarios. Build your own work with instructor guidance.
Regression Project
Predict future sales from realistic business features.
Deliverable: Regression notebook + forecast
Regression / MAE / Prediction. Understand the brief, apply the course skills, validate the result, and document your findings.
Classification Project
Predict which customers are at higher risk of leaving.
Deliverable: Churn model + retention insight
Classification / Recall / Confusion Matrix. Understand the brief, apply the course skills, validate the result, and document your findings.
Classification Project
Estimate which customers may respond to a campaign.
Deliverable: Response model + targeting list
Features / Probability / Precision. Understand the brief, apply the course skills, validate the result, and document your findings.
Evaluation Project
Compare models using appropriate metrics and validation.
Deliverable: Model scorecard + selection
Metrics / Validation / Tradeoffs. Understand the brief, apply the course skills, validate the result, and document your findings.
Mini Project
Investigate which features influence predictions most.
Deliverable: Feature report + chart
Importance / Correlation / Interpretation. Understand the brief, apply the course skills, validate the result, and document your findings.
Final project
Build, evaluate, and explain a predictive solution from a raw dataset.
Raw Data / Prepare / Train / Evaluate / Predict / Recommend
The program runs for 8 weeks, with Khmer and English instruction. Contact our team for the next start date, weekly timetable, and available places.
Ask about the next classLearn through guided explanations, class exercises, and feedback on your work. Your advisor can confirm the instructor and teaching schedule for your class.
Complete the required coursework and final project review to receive your Data Insight Cambodia certificate. Your projects help demonstrate the skills behind it.
Yes. Classes are instructor-led. After enrollment, Student Portal access provides class recordings, materials, assignments, and feedback to support your study between sessions.
This course builds on existing skills. Discuss your experience with an advisor before registering.
A course certificate is provided after you complete the required assignments and final project review.
No. We provide career guidance and project feedback. Employment and internships depend on available opportunities and employer requirements.
Contact an advisor
Ask about this course, class times, or how to register.